names(d)
## [1] "X" "unique" "chunk1" "chunk2"
## [5] "DecisionRT" "response" "DashedSentence1" "DashedSentence2"
## [9] "ID" "Letters" "Type" "TrialType"
## [13] "Number" "AnswerRelevance" "QUD" "AnswerConj1"
## [17] "AnswerConj2" "Conj" "trialRT" "Negation"
## [21] "QUDType"
nrow(d) #1440
## [1] 3426
length(unique(d$ID)) # 60 --> 48
## [1] 48
d$Mention <- ""
d$Mention[(d$Number == "1") |
(d$Number == "2") |
(d$Number == "7") |
(d$Number == "8")] <- "Mentioned"
d$Mention[(d$Number == "3") |
(d$Number == "4") |
(d$Number == "5") |
(d$Number == "6") |
(d$Number == "9") |
(d$Number == "10") |
(d$Number == "11") |
(d$Number == "12")] <- "NotMentioned"
d$AnswerQUDRelevant <- ""
d$AnswerQUDRelevant[(d$Number == "1") |
(d$Number == "2") |
(d$Number == "11") |
(d$Number == "12")] <- "NotQUDRelevant"
d$AnswerQUDRelevant[(d$Number == "3") |
(d$Number == "4") |
(d$Number == "5") |
(d$Number == "6") |
(d$Number == "7") |
(d$Number == "8") |
(d$Number == "9") |
(d$Number == "10")] <- "QUDRelevant"
agr <- d %>%
filter(Type =="critical") %>%
# is.numeric(DecisionRT) %>%
group_by(Letters,Conj,QUDType) %>% #AnswerQUDRelevant,Mention,QUDType
summarize(meanRT = mean(DecisionRT))
## `summarise()` regrouping output by 'Letters', 'Conj' (override with `.groups` argument)
# mutate(YMin = meanLogRT - CILow, YMax = meanLogRT + CIHigh)
ggplot(agr, aes(x = meanRT, fill=Conj, color=Conj)) +
geom_density(alpha = .4) +
facet_wrap(~QUDType)
# ggsave("graphs/denisty_QUD_rawRT.pdf",width=7,height=2)
ggplot(agr, aes(x=Conj, y=meanRT,fill=Conj, color=Conj)) +
geom_violin(trim=FALSE,alpha=.4) +
geom_jitter(shape=16, position=position_jitter(0.2)) +
facet_wrap(~QUDType)
agr <- d %>%
filter(Type =="critical") %>%
group_by(QUDType,Conj) %>%
summarize(meanRT = mean(DecisionRT), CILow = ci.low(DecisionRT), CIHigh = ci.high(DecisionRT)) %>%
mutate(YMin = meanRT - CILow, YMax = meanRT + CIHigh)
## `summarise()` regrouping output by 'QUDType' (override with `.groups` argument)
dodge <- position_dodge(.9)
ggplot(agr,aes(x=Conj, y=meanRT, fill=QUDType)) +
# facet_grid(Mention~AnswerQUDRelevant) +
geom_bar(position=dodge,stat="identity") +
geom_errorbar(aes(ymin=YMin,ymax=YMax),width=.25,position=dodge) +
# scale_fill_manual(values=cbPalette) +
# scale_color_manual(values=cbPalette) +
ggtitle("mean RT for Decision RT")
agr <- d %>%
filter(Type =="critical") %>%
# is.numeric(DecisionRT) %>%
group_by(Letters,Conj,QUDType,AnswerQUDRelevant) %>% #,Mention
summarize(meanRT = mean(DecisionRT))
## `summarise()` regrouping output by 'Letters', 'Conj', 'QUDType' (override with `.groups` argument)
# mutate(YMin = meanLogRT - CILow, YMax = meanLogRT + CIHigh)
ggplot(agr, aes(x = meanRT, fill=Conj, color=Conj)) +
geom_density(alpha = .4) +
facet_grid(AnswerQUDRelevant~QUDType)
# ggsave("graphs/denisty_QUDxRelevance_rawRT.pdf",width=6,height=3)
ggplot(agr, aes(x=Conj, y=meanRT,fill=Conj, color=Conj)) +
geom_violin(trim=FALSE,alpha=.4) +
geom_jitter(shape=16, position=position_jitter(0.2)) +
facet_grid(AnswerQUDRelevant~QUDType)
agr <- d %>%
filter(Type =="critical") %>%
group_by(QUDType,Conj,AnswerQUDRelevant) %>%
summarize(meanRT = mean(DecisionRT), CILow = ci.low(DecisionRT), CIHigh = ci.high(DecisionRT)) %>%
mutate(YMin = meanRT - CILow, YMax = meanRT + CIHigh)
## `summarise()` regrouping output by 'QUDType', 'Conj' (override with `.groups` argument)
dodge <- position_dodge(.9)
ggplot(agr,aes(x=Conj, y=meanRT, fill=QUDType)) +
facet_wrap(~AnswerQUDRelevant) +
geom_bar(position=dodge,stat="identity") +
geom_errorbar(aes(ymin=YMin,ymax=YMax),width=.25,position=dodge) +
# scale_fill_manual(values=cbPalette) +
# scale_color_manual(values=cbPalette) +
ggtitle("mean RT for Decision RT")
agr <- d %>%
filter(Type =="critical") %>%
# is.numeric(DecisionRT) %>%
group_by(Letters,Conj,QUDType,Mention) %>% #,Mention
summarize(meanRT = mean(DecisionRT))
## `summarise()` regrouping output by 'Letters', 'Conj', 'QUDType' (override with `.groups` argument)
# mutate(YMin = meanLogRT - CILow, YMax = meanLogRT + CIHigh)
ggplot(agr, aes(x = meanRT, fill=Conj, color=Conj)) +
geom_density(alpha = .4) +
facet_grid(Mention~QUDType)
# ggsave("graphs/denisty_QUDxMention_rawRT.pdf",width=6,height=3)
# Violn plot
ggplot(agr, aes(x=Conj, y=meanRT,fill=Conj, color=Conj)) +
geom_violin(trim=FALSE,alpha=.4) +
geom_jitter(shape=16, position=position_jitter(0.2)) +
facet_grid(Mention~QUDType)
# ggsave("../graphs/1a_violin.pdf",width=4,height=2)
agr <- d %>%
filter(Type =="critical") %>%
group_by(QUDType,Conj,Mention) %>%
summarize(meanRT = mean(DecisionRT), CILow = ci.low(DecisionRT), CIHigh = ci.high(DecisionRT)) %>%
mutate(YMin = meanRT - CILow, YMax = meanRT + CIHigh)
## `summarise()` regrouping output by 'QUDType', 'Conj' (override with `.groups` argument)
dodge <- position_dodge(.9)
ggplot(agr,aes(x=Conj, y=meanRT, fill=QUDType)) +
facet_wrap(~Mention) +
geom_bar(position=dodge,stat="identity") +
geom_errorbar(aes(ymin=YMin,ymax=YMax),width=.25,position=dodge) +
# scale_fill_manual(values=cbPalette) +
# scale_color_manual(values=cbPalette) +
ggtitle("mean RT for Decision RT")
agr <- d %>%
filter(Type =="critical") %>%
# is.numeric(DecisionRT) %>%
group_by(Letters,Conj,QUDType,Mention,AnswerQUDRelevant) %>% #,Mention
summarize(meanRT = mean(DecisionRT))
## `summarise()` regrouping output by 'Letters', 'Conj', 'QUDType', 'Mention' (override with `.groups` argument)
# mutate(YMin = meanLogRT - CILow, YMax = meanLogRT + CIHigh)
ggplot(agr, aes(x = meanRT, fill=Conj, alpha=QUDType, color=Conj)) +
geom_density(alpha = .4) +
facet_grid(AnswerQUDRelevant~Mention)
# ggsave("graphs/denisty_QUDxMention_rawRT.pdf",width=6,height=3)
# Violn plot
ggplot(agr, aes(x=Conj, y=meanRT,fill=Conj,alpha=QUDType,color=Conj)) +
geom_violin(trim=FALSE,alpha=.4) +
geom_jitter(shape=16, position=position_jitter(0.2)) +
facet_grid(AnswerQUDRelevant~Mention)
## Warning: Using alpha for a discrete variable is not advised.
# ggsave("../graphs/1a_violin.pdf",width=4,height=2)
agr <- d %>%
filter(Type =="critical") %>%
group_by(QUDType,Conj,AnswerQUDRelevant,Mention) %>%
summarize(meanRT = mean(DecisionRT), CILow = ci.low(DecisionRT), CIHigh = ci.high(DecisionRT)) %>%
mutate(YMin = meanRT - CILow, YMax = meanRT + CIHigh)
## `summarise()` regrouping output by 'QUDType', 'Conj', 'AnswerQUDRelevant' (override with `.groups` argument)
dodge <- position_dodge(.9)
ggplot(agr,aes(x=Conj, y=meanRT, fill=QUDType)) +
facet_grid(Mention~AnswerQUDRelevant) +
geom_bar(position=dodge,stat="identity") +
geom_errorbar(aes(ymin=YMin,ymax=YMax),width=.25,position=dodge) +
# scale_fill_manual(values=cbPalette) +
# scale_color_manual(values=cbPalette) +
ggtitle("mean RT for Decision RT")
agr <- d %>%
filter(Type =="critical") %>%
# is.numeric(DecisionRT) %>%
group_by(Letters,Conj,QUDType,Negation) %>% #,Mention
summarize(meanRT = mean(DecisionRT))
## `summarise()` regrouping output by 'Letters', 'Conj', 'QUDType' (override with `.groups` argument)
# mutate(YMin = meanLogRT - CILow, YMax = meanLogRT + CIHigh)
ggplot(agr, aes(x = meanRT, fill=Conj, color=Conj)) +
geom_density(alpha = .4) +
facet_grid(Negation~QUDType)
# ggsave("graphs/denisty_QUDxMention_rawRT.pdf",width=6,height=3)
# Violn plot
ggplot(agr, aes(x=Conj, y=meanRT,fill=Conj, color=Conj)) +
geom_violin(trim=FALSE,alpha=.4) +
geom_jitter(shape=16, position=position_jitter(0.2)) +
facet_grid(Negation~QUDType)
# ggsave("../graphs/1a_violin.pdf",width=4,height=2)
agr <- d %>%
filter(Type =="critical") %>%
group_by(QUDType,Conj,Negation) %>%
summarize(meanRT = mean(DecisionRT), CILow = ci.low(DecisionRT), CIHigh = ci.high(DecisionRT)) %>%
mutate(YMin = meanRT - CILow, YMax = meanRT + CIHigh)
## `summarise()` regrouping output by 'QUDType', 'Conj' (override with `.groups` argument)
dodge <- position_dodge(.9)
ggplot(agr,aes(x=Conj, y=meanRT, fill=QUDType)) +
facet_wrap(~Negation) +
geom_bar(position=dodge,stat="identity") +
geom_errorbar(aes(ymin=YMin,ymax=YMax),width=.25,position=dodge) +
# scale_fill_manual(values=cbPalette) +
# scale_color_manual(values=cbPalette) +
ggtitle("mean RT for Decision RT")
agr <- d %>%
filter(Type =="critical") %>%
# is.numeric(DecisionRT) %>%
group_by(Letters,Conj,QUDType,Negation,AnswerQUDRelevant) %>% #,Mention
summarize(meanRT = mean(DecisionRT))
## `summarise()` regrouping output by 'Letters', 'Conj', 'QUDType', 'Negation' (override with `.groups` argument)
# mutate(YMin = meanLogRT - CILow, YMax = meanLogRT + CIHigh)
ggplot(agr, aes(x = meanRT, fill=Conj, alpha=QUDType, color=Conj)) +
geom_density(alpha = .4) +
facet_grid(AnswerQUDRelevant~Negation)
# ggsave("graphs/denisty_QUDxMention_rawRT.pdf",width=6,height=3)
# Violn plot
ggplot(agr, aes(x=Conj, y=meanRT,fill=Conj,alpha=QUDType,color=Conj)) +
geom_violin(trim=FALSE,alpha=.4) +
geom_jitter(shape=16, position=position_jitter(0.2)) +
facet_grid(AnswerQUDRelevant~Negation)
## Warning: Using alpha for a discrete variable is not advised.
# ggsave("../graphs/1a_violin.pdf",width=4,height=2)
agr <- d %>%
filter(Type =="critical") %>%
group_by(QUDType,Conj,AnswerQUDRelevant,Negation) %>%
summarize(meanRT = mean(DecisionRT), CILow = ci.low(DecisionRT), CIHigh = ci.high(DecisionRT)) %>%
mutate(YMin = meanRT - CILow, YMax = meanRT + CIHigh)
## `summarise()` regrouping output by 'QUDType', 'Conj', 'AnswerQUDRelevant' (override with `.groups` argument)
dodge <- position_dodge(.9)
ggplot(agr,aes(x=Conj, y=meanRT, fill=QUDType)) +
facet_grid(Negation~AnswerQUDRelevant) +
geom_bar(position=dodge,stat="identity") +
geom_errorbar(aes(ymin=YMin,ymax=YMax),width=.25,position=dodge) +
# scale_fill_manual(values=cbPalette) +
# scale_color_manual(values=cbPalette) +
ggtitle("mean RT for Decision RT")
d$Number <- as.factor(d$Number)
agr <- d %>%
filter(Type =="critical") %>%
group_by(Number,QUDType) %>%
summarize(meanRT = mean(DecisionRT), CILow = ci.low(DecisionRT), CIHigh = ci.high(DecisionRT)) %>%
mutate(YMin = meanRT - CILow, YMax = meanRT + CIHigh)
## `summarise()` regrouping output by 'Number' (override with `.groups` argument)
# View(agr)
dodge <- position_dodge(.9)
ggplot(agr,aes(x=QUDType, y=meanRT, fill=QUDType)) +
facet_wrap(~Number,ncol=2) +
geom_bar(position=dodge,stat="identity") +
geom_errorbar(aes(ymin=YMin,ymax=YMax),width=.25,position=dodge)
# scale_fill_manual(values=cbPalette) +
# scale_color_manual(values=cbPalette) +
# ggtitle("mean RT for Decision RT")
agr <- d %>%
filter(Type =="critical") %>%
filter(Number %in% c("7","8","1","2")) %>%
group_by(Number,QUDType) %>%
summarize(meanRT = mean(DecisionRT), CILow = ci.low(DecisionRT), CIHigh = ci.high(DecisionRT)) %>%
mutate(YMin = meanRT - CILow, YMax = meanRT + CIHigh)
## `summarise()` regrouping output by 'Number' (override with `.groups` argument)
dodge <- position_dodge(.9)
ggplot(agr,aes(x=Number, y=meanRT, fill=QUDType)) +
# facet_wrap(~Number) +
geom_bar(position=dodge,stat="identity") +
geom_errorbar(aes(ymin=YMin,ymax=YMax),width=.25,position=dodge) +
# scale_fill_manual(values=cbPalette) +
# scale_color_manual(values=cbPalette) +
ggtitle("mean RT for Decision RT, 7/8, 1/2")
troublesome cases: 1: EBT,LHN 2: TYK,IYG 7: JLP, XDS 8: QDR, UOP
irel rel 1: EBT “There is no cue, and there is a T” 1’: LHN “There is no P and there is an H” <<< lower mean
2: TYK: “There is no L, but there is a K” 2’: IYG “There is no X but there is an I”
rel rel 7: JLP “There is no U and there is a J” 7’: XDS “There is no O and there is an X”
8: QDR “There is no V but there is a D” 8’: UOP “There is no F but there is a U”
agr <- d %>%
filter(Type =="critical") %>%
filter(Number %in% c("7","8","1","2")) %>%
# is.numeric(DecisionRT) %>%
group_by(QUDType,Letters) %>%
summarize(meanRT_DecisionRT = mean(DecisionRT), CILow = ci.low(DecisionRT), CIHigh = ci.high(DecisionRT)) %>%
mutate(YMin = meanRT_DecisionRT - CILow, YMax = meanRT_DecisionRT + CIHigh)
## `summarise()` regrouping output by 'QUDType' (override with `.groups` argument)
# reoder the levels so that we can see side-by-side the comparisons
agr$Letters <- factor(agr$Letters, levels=c("EBT","LHN","TYK","IYG","JLP","XDS","QDR","UOP"))
dodge <- position_dodge(.9)
ggplot(agr,aes(x=Letters, y=meanRT_DecisionRT,alpha=QUDType, fill=Letters)) +
# facet_wrap(~QUDType, ncol=3) +
# facet_wrap(~Wh, ncol=2) +
geom_bar(position=dodge,stat="identity") +
geom_errorbar(aes(ymin=YMin,ymax=YMax),width=.25,position=dodge) +
# scale_fill_manual(values=cbPalette) +
# scale_color_manual(values=cbPalette) +
ggtitle("mean RT for Decision RT, individual trials in order 1, 2, 7, 8")
## Warning: Using alpha for a discrete variable is not advised.
# Look at the Decision RT reading time
agr <- d %>%
filter(Type =="critical") %>%
filter(Number %in% c("3","4","5","6","9","10","11","12")) %>%
# is.numeric(DecisionRT) %>%
group_by(QUDType,Number) %>%
summarize(meanRT_DecisionRT = mean(DecisionRT), CILow = ci.low(DecisionRT), CIHigh = ci.high(DecisionRT)) %>%
mutate(YMin = meanRT_DecisionRT - CILow, YMax = meanRT_DecisionRT + CIHigh)
## `summarise()` regrouping output by 'QUDType' (override with `.groups` argument)
# reoder the levels so that we can see side-by-side the comparisons
# df_DecisionRT$Letters <- factor(df_DecisionRT$Letters, levels=c("EBT","LHN","TYK","IYG","JLP","XDS","QDR","UOP"))
dodge <- position_dodge(.9)
ggplot(agr,aes(x=QUDType, y=meanRT_DecisionRT, fill=QUDType)) +
facet_wrap(~Number, ncol=2) +
# facet_wrap(~Wh, ncol=2) +
geom_bar(position=dodge,stat="identity") +
geom_errorbar(aes(ymin=YMin,ymax=YMax),width=.25,position=dodge) +
# scale_fill_manual(values=cbPalette) +
# scale_color_manual(values=cbPalette) +
ggtitle("mean RT for Decision RT, individual trials in order 3-6, 9-12")
# Look at the Decision RT reading time
agr <- d %>%
filter(Type =="critical") %>%
filter(Number %in% c("3","4","5","6","9","10","11","12")) %>%
# is.numeric(DecisionRT) %>%
group_by(QUDType,Letters) %>%
summarize(meanRT_DecisionRT = mean(DecisionRT), CILow = ci.low(DecisionRT), CIHigh = ci.high(DecisionRT)) %>%
mutate(YMin = meanRT_DecisionRT - CILow, YMax = meanRT_DecisionRT + CIHigh)
## `summarise()` regrouping output by 'QUDType' (override with `.groups` argument)
# reoder the levels so that we can see side-by-side the comparisons
agr$Letters <- factor(agr$Letters, levels=c(
# 3/4
"ZFW","MCR",
# 3'/4'
"BQG","DNF",
# 5/6
"VGW","PBN",
# 5'/6'
"OTY","JXO",
# 9/10
"FQA","RUI",
# 9'/10'
"AKT","NJV",
# 11/12
"XAV","CEH",
# 11'/12'
"ZDY","IFL"))
dodge <- position_dodge(.9)
ggplot(agr,aes(x=QUDType, y=meanRT_DecisionRT, fill=QUDType)) +
facet_wrap(~Letters, ncol=2) +
# facet_wrap(~Wh, ncol=2) +
geom_bar(position=dodge,stat="identity") +
geom_errorbar(aes(ymin=YMin,ymax=YMax),width=.25,position=dodge) +
# scale_fill_manual(values=cbPalette) +
# scale_color_manual(values=cbPalette) +
ggtitle("mean RT for Decision RT, individual trials in order 3-6, 9-12")
dodge <- position_dodge(.9)
ggplot(agr,aes(x=QUDType, y=meanRT_DecisionRT, fill=Letters)) +
# facet_wrap(~Letters, ncol=2) +
# facet_wrap(~Wh, ncol=2) +
geom_bar(position=dodge,stat="identity") +
geom_errorbar(aes(ymin=YMin,ymax=YMax),width=.25,position=dodge) +
# scale_fill_manual(values=cbPalette) +
# scale_color_manual(values=cbPalette) +
ggtitle("mean RT for Decision RT, individual trials in order 3-6, 9-12")
agr <- d %>%
filter(Type =="critical") %>%
# is.numeric(DecisionRT) %>%
group_by(QUDType,Conj,AnswerQUDRelevant,Mention) %>%
summarize(meanLogRT = mean(log(DecisionRT)), CILow = ci.low(log(DecisionRT)), CIHigh = ci.high(log(DecisionRT))) %>%
mutate(YMin = meanLogRT - CILow, YMax = meanLogRT + CIHigh)
## `summarise()` regrouping output by 'QUDType', 'Conj', 'AnswerQUDRelevant' (override with `.groups` argument)
# View(df_DecisionRT)
dodge <- position_dodge(.9)
ggplot(agr,aes(x=Conj, y=meanLogRT, fill=QUDType)) +
facet_grid(Mention~AnswerQUDRelevant) +
geom_bar(position=dodge,stat="identity") +
geom_errorbar(aes(ymin=YMin,ymax=YMax),width=.25,position=dodge) +
# scale_fill_manual(values=cbPalette) +
# scale_color_manual(values=cbPalette) +
ggtitle("mean logRT for Decision RT")
agr <- d %>%
filter(Type =="critical") %>%
# is.numeric(DecisionRT) %>%
group_by(Letters,Conj,QUDType) %>% #AnswerQUDRelevant,Mention,QUDType
summarize(meanLogRT = mean(log(DecisionRT)))
## `summarise()` regrouping output by 'Letters', 'Conj' (override with `.groups` argument)
# mutate(YMin = meanLogRT - CILow, YMax = meanLogRT + CIHigh)
ggplot(agr, aes(x = meanLogRT, fill=Conj, color=Conj)) +
geom_density(alpha = .4) +
facet_wrap(~QUDType)
# ggsave("graphs/denisty_QUD_logRT.pdf",width=7,height=2)